Short-chain fatty acids and insulin sensitivity: a systematic review and meta-analysis

Abstract Context There is substantial evidence that reduced short-chain fatty acids (SCFAs) in the gut are associated with obesity and type 2 diabetes, although findings from clinical interventions that can increase SCFAs are inconsistent. Objective This systematic review and meta-analysis aimed to assess the effect of SCFA interventions on fasting glucose, fasting insulin, and homeostatic model assessment of insulin resistance (HOMA-IR). Data Sources Relevant articles published up to July 28, 2022, were extracted from PubMed and Embase using the MeSH (Medical Subject Headings) terms of the defined keywords [(short-chain fatty acids) AND (obesity OR diabetes OR insulin sensitivity)] and their synonyms. Data analyses were performed independently by two researchers who used the Cochrane meta-analysis checklist and the PRISMA guidelines. Data Extraction Clinical studies and trials that measured SCFAs and reported glucose homeostasis parameters were included in the analysis. Standardized mean differences (SMDs) with 95%CIs were calculated using a random-effects model in the data extraction tool Review Manager version 5.4 (RevMan 5.4). The risk-of-bias assessment was performed following the Cochrane checklist for randomized and crossover studies. Data Analysis In total, 6040 nonduplicate studies were identified, 23 of which met the defined criteria, reported fasting insulin, fasting glucose, or HOMA-IR values, and reported change in SCFA concentrations post intervention. Meta-analyses of these studies indicated that fasting insulin concentrations were significantly reduced (overall effect: SMD = −0.15; 95%CI = −0.29 to −0.01, P = 0.04) in treatment groups, relative to placebo groups, at the end of the intervention. Studies with a confirmed increase in SCFAs at the end of intervention also had a significant effect on lowering fasting insulin (P = 0.008). Elevated levels of SCFAs, compared with baseline levels, were associated with beneficial effects on HOMA-IR (P < 0.00001). There was no significant change in fasting glucose concentrations. Conclusion Increased postintervention levels of SCFAs are associated with lower fasting insulin concentrations, offering a beneficial effect on insulin sensitivity. Systematic Review Registration PROSPERO registration number CRD42021257248.


INTRODUCTION
Type 2 diabetes mellitus (T2DM) is characterized by a reduction in b-cell function as well as by insulin resistance, wherein skeletal muscle, liver, and adipocytes cannot uptake sufficient amounts of glucose. 1 It leads to life-threatening complications such as neuropathy, retinopathy, and cardiovascular disease.According to the World Health Organization, there are over 537 million adults living with T2DM, and this number is estimated to reach 783 million by 2045. 2 Along with T2DM, overweight (body mass index [BMI] of 25 to < 30 kg/m 2 ) and obesity (BMI !30) are considered major health problems, currently affecting approximately 2 billion people worldwide. 3,4Obesity is a major risk factor for the development of cardiovascular disease, hypertension, and stroke.It is also known to dramatically increase the risk of T2DM, as 90% of individuals with T2DM are obese or overweight. 5Beneficial effects of gut microbiota and short-chain fatty acids (SCFAs) on metabolic health in obesity 6,7 and T2DM 8,9 have been reported.Differences of the diversity of the gut microbiome are well recognized between lean and obese individuals 6,7 as well as between individuals with and without diabetes. 10,11Gut microbes produce SCFAs, mainly acetate, propionate, and butyrate, through the fermentation of resistant starch or soluble fiber.These molecules induce the expression of gut hormones such as peptide tyrosine-tyrosine (PYY) and glucagon-like peptide 1 (GLP-1) via free fatty acid receptors (G-protein-coupled receptors 41 and 43), 12,13 leading to appetite suppression 14 and improvement of glucose tolerance and insulin sensitivity. 15,16In addition, fecal transplantation from lean donors to obese recipients altered the gut microbial composition and improved insulin sensitivity in the recipients. 17,18hort-chain fatty acids can be administered directly, as sodium salts or esters, or indirectly, as pre-/probiotics or high-fiber diets.Multiple clinical trials have aimed at increasing SCFA levels in participants with impaired insulin sensitivity, preexisting overweight/obesity, or multiple gastrointestinal abnormalities.Many metaanalyses of SCFAs in human clinical trials are available, but most of these focus on irritable bowel disease, [19][20][21] inflammatory markers, 22,23 obesity, 24,25 or gut biota. 26,27elevant previous meta-analyses (see Table S1 in the Supporting Information online) report effects on insulin and glucose concentrations after consumption of specific diets such as those high in fiber, resistant starch or whole grains, or synbiotics and probiotics.Only one review analyzed changes in total SCFAs, along with levels of Bifidobacteria and fasting glucose; however, it did not examine the effect of SCFA changes on fasting insulin or homeostatic model assessment of insulin resistance (HOMA-IR).Until now, there is no systematic review and meta-analysis that assessed the effects of postintervention changes in SCFAs on insulin sensitivity in humans.To address this research gap, clinical studies (randomized clinical trials, observational studies, or treatment-only studies) that reported actual values of glucose, insulin, or HOMA-IR and that measured SCFAs following interventions were analyzed.This systematic review and meta-analysis includes different interventions that have the potential to alter SCFAs and is focused on studies that confirm a change in SCFA concentrations post intervention.

Literature search
A systematic search was carried out using PubMed and Embase via Ovid for studies published from January 1, 1959, to July 28, 2022.There were no restrictions on the use of MeSH (Medical Subject Heading) terms and their synonyms.The keywords used for the literature search were "short-chain fatty acids" AND ("obesity" OR "diabetes" OR "insulin sensitivity").All studies were screened by title, abstract, and full-text reading (Figure 1), following the Cochrane meta-analysis checklist and the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines 28 (see Appendix S1 in the Supporting Information online).Descriptions of search strategy, study eligibility, data extraction, and analysis of this systematic review were preregistered in the PROSPERO system (ID no.CRD42021257248).

Inclusion and exclusion criteria
Papers were included for screening if they contained the keywords (as defined in the Literature search section above) and met the PICOS (Participants, Intervention, Comparator, Outcomes, Study design) criteria summarized in Table 1.The following exclusion criteria were applied: (1) studies other than human studies, such as animal studies or cell culture studies, (2) studies not published in the English language, and (3) publication types other than peer-reviewed original papers, such as systematic reviews, meta-analyses, reviews, conference publications, non-article papers, generic writing, theses or chapters, and case reports, (4) studies not providing data for fasting glucose, fasting insulin, or HOMA-IR, and (5) studies not reporting pre-and postintervention SCFA changes.

Data extraction
Results of the literature search were added to an EndNote X8 29 library and entered into an MS Excel worksheet for data screening and extraction (Figure 1).The first step of removing duplicate hits from the two databases (Embase and PubMed) was performed in the EndNote library, where papers with identical titles and authors were marked as duplicates and removed.In the screening step, titles and abstracts were assessed for eligibility, and articles were excluded if they met any of the exclusion criteria.The full-text versions of the 23 qualifying papers that met the inclusion criteria (original clinical studies in humans; provided values, not area under the curve [AUC] values or coefficients) of fasting  glucose or fasting insulin or the HOMA-IR score; and reported change in plasma or fecal SCFAs before and after the intervention were then reviewed and included in the meta-analysis.All values were converted to mean 6 standard deviation (SD) for glucose (mmol/L) and insulin (lU/mL).Reported units for glucose and insulin were made consistent. 30In 2 of the 23 studies, 31,32 units or standard deviation values were confirmed with the authors of the original articles via E-mail correspondence.Subgroup analyses were performed to investigate differences in fasting insulin, glucose, or HOMA-IR between placebo and treatment groups, or between the baseline and the endpoint.Two researchers (N.H.T.P. and M.V.J.) performed the search and data extraction independently and then cross-checked the results.

Quality of evidence and risk of bias
Risk of bias and the quality of evidence were assessed in accordance with the Cochrane recommendations, 33 and outcomes were presented using RevMan software, version 5.4. 34The criteria included random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective bias (reporting bias), and other bias.Each criterion was graded as having high, low, or unclear risk of bias.Treatment-only studies were not evaluated for selection, performance, or detection bias because all participants and associated clinicians were aware of the treatment allocation.Several of the studies had a crossover design.Therefore, 3 additional criteria for crossover studies were assessed: appropriate crossover design, carryover effects, and unbiased data (reporting of data at all stages of the trial). 35

Data synthesis and statistical analysis
Data synthesis and statistical analysis were carried out using Microsoft Excel and RevMan 5.4 software.Microsoft Excel was used to tabulate and summarize the insulin and glucose values at appropriate units.RevMan 5.4 was used to produce forest plots.All data were entered as mean 6 SD.The random-effects model and the inverse variance statistical method were used to calculate standardized mean differences (SMDs) with 95%CIs between the placebo group and the intervention group, or between the baseline and the endpoint.The same analysis was also carried out using the fixed-effects model to ensure the robustness of the calculations.All the analyses were performed in RevMan 5.4.A P value < 0.05 was considered significant.Standardized mean difference values for SCFAs, insulin, and glucose were calculated in RevMan 5.4 and used for Spearman correlation analysis.A correlation matrix was generated using the corrplot (version 0.92), Hmisc (version 4.6-0), and dplyr (version 1.0.7)packages and R (version 3.6.1) in Rstudio (version 2021.09.0,Build 351; R Foundation for Statistical Computing, Vienna, Austria).The correlation significance was analyzed and verified on GraphPad Prism version 9.4.1 (GraphPad Software; San Diego, CA, USA).

Characteristics of studies included in meta-analysis
Figure 1 shows the PRISMA flow diagram for the stepwise selection of studies.The initial search using the defined MeSH terms in PubMed and Embase via Ovid identified 6040 papers (after excluding 907 duplicates).During screening, 570 papers were removed because they were not published in English or were non-journal articles.After the remaining 5470 papers were screened by title and abstract, 278 were deemed eligible for fulltext assessment.A majority of these studies (n ¼ 198) were excluded because insulin sensitivity/resistance tests were not performed, while another 49 did not present quantitative data on fasting insulin or fasting glucose.The 23 studies that contained actual values for fasting glucose and insulin were included in the metaanalysis (Table 2 31,32, ).
a Reported per the original article.

Effects of SCFAs on glucose homeostasis parameters between placebo and intervention groups at the endpoint
The effects of SCFAs on fasting insulin (Figure 2), fasting glucose (Figure 3), and HOMA-IR (Figure 4) are stratified for studies (from Table 2) that confirm a significant increase or no change in SCFA concentrations post intervention.In a comparison between placebo and intervention groups at the endpoint (final assessment after intervention), fasting insulin was significantly lower (SMD ¼ À0.25; 95%CI ¼ À0.43 to À0.06; P ¼ 0.008) in the treatment group when SCFA concentrations were confirmed to have increased at the end of the intervention (Figure 2).The overall effect on fasting insulin concentrations was also significant (SMD ¼ À0.15; 95%CI ¼ À0.29 to À0.01; P ¼ 0.04; Figure 2).In contrast, fasting glucose (SMD ¼ À0.06; 95%CI ¼ À0.24 to 0.13; P ¼ 0.55; Figure 3) and HOMA-IR (SMD ¼ À0.22; 95%CI ¼ À0.48 to 0.05; P ¼ 0.11; Figure 4) did not differ significantly between treatment and control arms for studies wherein SCFA concentrations increased post intervention.For the subgroup of studies that did not show an increase in SCFAs, there were no significant differences in fasting insulin, fasting glucose, or HOMA-IR between the control and treatment arms (Figures 2, 3, and 4).

Risk-of-bias assessment
The quality assessment of the 23 studies included in the meta-analysis is presented in Figure S8 in the Supporting Information online.7][48]52,53 Several of the studies did not report sufficient details of unbiased data presentation or carryover effects to assign low or high risks, and thus they had to be classified as having unclear risk of bias.Eight studies did not describe allocation concealment, the criterion with the highest factor of unclear risk.Similarly, most studies did not have clear reporting of unbiased data (availability of study results at every time point during crossover).The risk of bias for blinding criteria was high in 6 studies.Since most of the studies were dietary interventions, blinding may not have been always applicable (eg, when the participants and the researchers could see which foods were given).In the parallel-arm trials, the risk of bias was much lower in most of the studies (see Figure S8-B in the Supporting   Information online).Five treatment-only studies were not included in the analysis of selection, performance, or detection bias because all participants received the same treatment, and any selection/blinding was not applicable.These studies are represented by the white area in the graph (see Figure S8-B in the Supporting Information online).

DISCUSSION
This systematic review and meta-analysis of 23 studies included a varied group of participants.The main finding was significantly lower fasting insulin in the group that received SCFAs directly and in the group that had evidence of an increase in SCFAs following intervention compared with the placebo group.When baseline and endpoint values were compared in the treatment groups, fasting insulin and HOMA-IR were significantly improved at the endpoint, a finding not observed for the baseline vs endpoint comparison in the placebo groups.Similar results were achieved when using the fixed-effects model, thus confirming the robustness of this study.
The underlying mechanism linking SCFAs to T2DM has not been fully elucidated.A mechanism involving gut microbes or microbial metabolites (eg, colonic SCFAs) regulating incretin hormone expression, insulin secretion, and glucose homeostasis is likely and needs validation.Incretin hormones such as glucose-dependent insulinotropic polypeptide and GLP-1 are known to regulate insulin secretion following oral glucose intake. 57Glucagon-like peptide 1 also plays a significant role in improving glucose tolerance and insulin sensitivity. 15,16Interestingly, SCFAs lowered fasting insulin and improved HOMA-IR without affecting fasting glucose.It would have been informative to understand the effects of the increase in SCFAs on GLP-1 concentrations, but only 6 studies measured GLP-1, [38][39][40]49,52,53 and only 3 of these studies mentioned the use of the necessary dipeptidyl peptidase 4 inhibitors during the collection of samples. 39,52,53Metaanalysis to understand the effect of changes in SCFAs on GLP-1 was inconclusive in this same set of papers.
][60][61] Notably, most of the studies conducted during the last decade have focused on the oral administration of sodium propionate, sodium butyrate, or SCFA mixtures for extended periods of time (up to 6 months), with dosages ranging from 1 to 10 g/d.These studies and the long periods of SCFA intervention underscore the safety of SCFAs in human clinical studies/trials.To date, there have been no reports of any adverse effects of SCFAs on human health.A very recent systematic review and meta-analysis assessed the effects of acute and chronic administration of SCFAs and vinegar on glycemic control. 62Interestingly, the authors did not observe a significant effect of acute acetate or propionate treatment or chronic propionate treatment on glucose and insulin concentrations.However, they did not stratify their analyses on the basis of changes in SCFA concentrations post intervention.The quantitative analysis showed that only those studies with evidence of an increase in SCFA concentrations reported significantly lower fasting insulin values.Studies without any increase in SCFAs reported no change in insulin concentrations.
Short-chain fatty acids are typically measured in fecal or plasma samples.They are present in larger quantities in feces, 63 and fecal SCFAs are considered to be an indirect representation of SCFA production in the colon.Short-chain fatty acids in the circulation are present in smaller quantities and usually reflect the amount remaining after uptake into colonocytes and then the liver. 64Nonetheless, circulating SCFAs are shown to be more directly associated with metabolic health than fecal SCFAs. 65The subanalysis also confirmed a significant effect of SCFAs on fasting insulin concentrations when circulating SCFAs are increased.One potential reason for higher variability in fecal SCFAs could be the variations in methods used for collection, storage, and processing of samples. 66tandardization of methods for measurement of SCFAs is urgently needed.
The present meta-analysis demonstrates that direct administration of SCFAs is more beneficial than indirect methods of administration, including a variety of diets.It is notable that SCFAs are not well suited to oral administration because of their unpleasant taste and odor. 67Recent studies have focused on the development of novel targeted delivery systems that can deliver SCFAs into the colon or the circulatory system. 68Only one study in the present systematic review investigated the direct infusion of SCFAs (ie, acetate), reporting increases in circulating (plasma/serum) SCFAs. 31All the remaining studies that provided SCFAs as capsules, powders, or meals reported variable SCFA concentrations at the endpoint. 38,40,41,56part from potential differences in fecal and circulating SCFA concentrations, another reason for this variation could be different methods of assessing compliance.Three trials maintained regular communication between participants and investigators to encourage high compliance, and the participants returned their used and unused sachets to calculate the compliance rate at the end of the study. 40,41,56Future studies should ensure that compliance with the intervention is assessed and reported.
Because of the invasive nature of infusion studies, the direct infusion of acetate was performed for only a short period of time. 3153][54]56 Therefore, it would be interesting to understand the long-term effects of SCFA infusion on insulin sensitivity.Clinical trials addressing this question are warranted.Interestingly, a separate systematic review and meta-analysis confirmed that the left colon may contribute to the maintenance of glucose homeostasis. 69Since human GLP-1-producing L cells are found at the highest density in the left colon, 70 removal of the left colon is, not surprisingly, associated with T2DM.The direct infusion of SCFAs provides a unique opportunity to manipulate the expression of incretin hormones, and more studies in this area are needed.
Dietary fiber (from whole grain, oat/wheat/barley bran, guar gum, pectin, legumes, psyllium, and resistant starch) enhances the production of SCFAs in the colon following fermentation by gut microbes. 71,72Although the beneficial effects of dietary fiber intake on obesity and diabetes have been highlighted, 73,74 this metaanalysis provides evidence for the beneficial role of SCFA interventions in lowering fasting hyperinsulinemia (see Figures S1 and S2 in the Supporting Information online).Short-chain fatty acids are naturally available through fermented beverages and food products, such as apple cider vinegar, kombucha, fermented alcoholic beverages, kefir, cheese, legumes, nuts/seeds, soybean paste, ghee, sauerkraut, and pickled vegetables. 75,76These food products contain high levels of SCFAs, are easy to obtain, and provide readily available dietary sources of SCFAs.Daily SCFA consumption (in moderation) through SCFA-rich food products may hold great potential to improve insulin sensitivity and provide substantial health benefits, including reducing the risk of cancer. 77Larger clinical studies investigating the effects of these fermented beverages and food products are warranted.
The limitations of this meta-analysis are mainly due to the heterogeneity of the included studies, which was unavoidable because of the nature of the study question around the effect of SCFAs on insulin sensitivity.The factors contributing to the high heterogeneity were age, sex, sample size, diet, lifestyle, underlying health conditions, types of SCFAs measured (acetate, propionate, butyrate, or all), and the source of SCFAs (feces or plasma).Other sources of heterogeneity include the different types of interventions used, such as various diets, gastric bypass surgery, or SCFAs provided as capsules or via infusion.It was not possible to perform subgroup analyses to understand the effects of SCFA dosage or SCFA delivery route on fasting insulin and fasting glucose because the number of studies was too low.It is also notable that majority of the studies in this analysis were conducted on 3 different continents (Europe, North America, and Australia), which may have contributed to the risk of bias through the recruitment of the majority of individuals of only one ethnicity.However, the ethnicity of participants was not mentioned in any of the studies.The included studies reported differences in sensitivities of the methods used for measurement of SCFAs and insulin or glucose.In addition, the literature search was limited to papers published in English, and thus 169 non-English papers were excluded.
Despite its limitations, this systematic review is the first to summarize and provide a meta-analysis of clinical studies showing the beneficial effects of increased SCFAs on fasting insulin and HOMA-IR.This metaanalysis captured all studies that reported SCFA changes and provided actual values of fasting insulin and glucose in humans.This approach was chosen as the focus of the systematic review and meta-analysis in order to increase current understanding of the metabolic benefits of elevated SCFAs following clinical interventions.

CONCLUSION
This is the first meta-analysis to demonstrate a significant decrease in fasting insulin when SCFA concentrations were confirmed to have increased.While this beneficial effect of SCFAs on fasting insulin has been confirmed, several factors need to be evaluated before optimal implementation of SCFA interventions, such as the type of SCFA (acetate, propionate, butyrate, or a mixture), the form of SCFA administration (fiberenriched diets or capsules containing sodium salts or inulin esters), the duration of intervention, the route of delivery (oral or intravenous infusion), and patient compliance.Nonetheless, on the basis of the overall results presented here, direct SCFA consumption or an SCFA-enriched diet was found to have beneficial effects on fasting insulin concentrations.Therefore, SCFA interventions, or dietary guidance along with clinical monitoring and lifestyle management, could be considered a safe and novel treatment for individuals with overweight, obesity, or T2DM.
Technology Sydney, Sydney, New South Wales, Australia.
Author contributions.A.A.H. conceptualized the study; N.H.T.P. conducted the literature search and data analysis; M.V.J. validated the literature search and contributed to data interpretation and analysis; W.K.M.W. performed correlation data analysis; N.T.N. and A.M.S. participated in data interpretation and analysis; N.H.T.P. and M.V.J. wrote the first draft; W.K.M.W., N.T.N., A.M.S., and A.A.H. wrote and edited the manuscript; A.A.H. finalized the manuscript; and all authors contributed revisions to the manuscript.All authors read the final version of the manuscript submitted for publication.A.A.H. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Supporting Information
The following Supporting Information is available through the online version of this article at the publisher's website.
Appendix S1 PRISMA 2020 checklist.Table S1 Previously published relevant metaanalyses and systematic reviews assessing the effects of diet, pre-/pro-/synbiotics on insulin and glucose metabolism.
Table S2 Concentrations of short-chain fatty acids (SCFAs) reported in different studies for placebo and treatment groups at the end of intervention.
Figure S1 Forest plot of fasting insulin concentrations between control group and treatment subgroup by direct or indirect administration of short-chain fatty acids.
Figure S2 Forest plot of fasting insulin concentrations between control group and treatment subgroup by direct or indirect administration of short-chain fatty acids (SCFAs) and by increase or no increase in SCFAs.
Figure S3 Forest plot of fasting insulin concentrations between control group and treatment subgroup by measurement of plasma or fecal short-chain fatty acids (SCFAs) and by increase or no increase in SCFAs.
Figure S4 Correlation matrix between changes in concentrations of fasting insulin, fasting glucose, and different short-chain fatty acids.
Figure S5 Forest plot of fasting insulin concentrations between baseline and endpoint in placebo group.
Figure S6 Forest plot of fasting glucose concentrations between baseline and endpoint in placebo group.
Figure S7 Forest plot of homeostatic model assessment of insulin resistance (HOMA-IR) between baseline and endpoint in placebo group.
Figure S8 Risk-of-bias analysis.

Figure 1
Figure 1 Flow diagram of the literature search process.

Figure 2
Figure 2 Fasting insulin concentrations from each study were compared between placebo group and treatment group at the end of the intervention period.Data are presented as the standardized mean difference (SMD) in fasting insulin (mU/mL) and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate) is noted at the end of each study.Abbreviation: IV, inverse variance.

Figure 3
Figure 3 Fasting glucose concentrations from each study were compared between placebo group vs treatment group at the end of the intervention period.Data are presented as the standardized mean difference (SMD) in fasting glucose (mmol/L) and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate) is noted at the end of each study.Abbreviation: IV, inverse variance.

Figure 4
Figure 4 Homeostatic model assessment of insulin resistance (HOMA-IR) values were compared between placebo group and treatment group at the end of the intervention period.Data are presented as the standardized mean difference (SMD) in HOMA-IR and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate) is noted at the end of each study.Abbreviation: IV, inverse variance.

Figure 5
Figure 5 Fasting insulin concentrations at baseline and endpoint (end of intervention) from each study in the treatment group.Data are presented as the standardized mean difference (SMD) in fasting insulin (mU/mL) and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate; C2, acetate) is noted at the end of each study.Abbreviation: IV, inverse variance.

Figure 6
Figure 6 Fasting glucose concentrations at baseline and endpoint (end of intervention) from each study in the treatment group.Data are presented as the standardized mean difference (SMD) in fasting insulin (mmol/L) and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate; C2, acetate) is noted at the end of each study.Abbreviation: IV, inverse variance.

Figure 7
Figure 7 Homeostatic model assessment of insulin resistance (HOMA-IR) values at baseline and endpoint (end of intervention) from available studies in the treatment group.Data are presented as the standardized mean difference (SMD) in HOMA-IR and have been separated into two subgroups: one with evidence of an increase in short-chain fatty acids (SCFAs) concentration(s) post intervention, and the other without any change in SCFAs post intervention.The type of intervention (M, meal/mixed; C3, propionate) is noted at the end of each study.Abbreviation: IV, inverse variance.
Funding.N.H.T.P. acknowledges a scholarship from the Diabetes and Islet Biology Group and support through Diabetes Australia (General Grant to M.V.J.).M.V.J. was supported through a Juvenile Diabetes Research Foundation (JDRF) International Advanced Postdoctoral Fellowship (3-APF-2016-178-A-N) and a Transition Award from JDRFI (1-FAC-2021-1063-A-N).W.K.M.W. is supported through the Leona M. and Harry B. Helmsley Charitable Trust (Grant 2018PG-T1D009 to AAH) in collaboration with the JDRF Australian Type 1 Diabetes Clinical Research Network funding (Grant 3-SRA-2019-694-M-B to A.A.H.).A.A.H. is supported by grants from the JDRF Australia Type 1 Diabetes Clinical Research Network (JDRF/4-CDA2016-228-MB) and Visiting Professorships (2016-18 and 2019-22) from the Danish Diabetes Academy, funded by the Novo Nordisk Foundation, grant number NNF17SA0031406.Declaration of interest.The authors have no relevant interests to declare.

Table 1
PICOS criteria for inclusion and exclusion of studies AUC, area under the curve; SCFAs, short-chain fatty acids; HOMA-IR, homeostatic model assessment of insulin resistance; IV, intravenous.
ParticipantsHealthy adults, obese/overweight adults, or adults with underlying conditions Animal and in vitro cellular studies Interventions Direct SCFAs interventions (oral/IV infusion/ enema of sodium acetate, propionate, or butyrate, alone or mixed) or dietary supplementation (resistant starch, inulin, or chemically modified fiber) Direct supplementation with substances other than the 3 SCFAs (acetate, propionate, or butyrate)

Table 2
Details of the 23 studies included in the meta-analysis Nutrition Reviews V R Vol. 82(2):193-209

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